Probing the Viscoelastic Properties of Aqueous Protein Solutions using Molecular Dynamics Simulations

TL;DR

This study uses molecular dynamics simulations to explore how temperature and protein concentration affect the viscoelastic properties of aqueous protein solutions, aligning well with experimental observations and advancing understanding of these complex systems.

Contribution

The paper demonstrates the effectiveness of molecular dynamics simulations in accurately predicting the viscoelastic behavior of protein solutions across various conditions, validating simulation approaches against experimental data.

Findings

Lower temperatures increase viscosity and decrease bulk modulus and speed of sound.

Increasing temperature up to a point raises bulk modulus and speed of sound while decreasing viscosity.

Higher protein concentration enhances bulk modulus, speed of sound, and viscosity.

Abstract

We performed molecular dynamics simulations to investigate the viscoelastic properties of aqueous protein solutions containing an antifreeze protein, a toxin protein, and bovine serum albumin. These simulations covered a temperature range from 280 K to 340 K. Our findings demonstrate that lower temperatures are associated with higher viscosity as well as a lower bulk modulus and speed of sound for all the systems studied. Furthermore, we observe an increase in the bulk modulus and speed of sound as the temperature increases up to a weak maximum while the viscosity decreases. Moreover, we analyzed the influence of protein concentration on the viscoelastic properties of the antifreeze protein solution. We observed a consistent increase in the bulk modulus, speed of sound, and viscosity as the protein concentration increased. Remarkably, our molecular dynamics simulations results closely resemble the trends observed in Brillouin scattering experiments on aqueous protein solutions. The similarity thus validates the use of simulations in studying the viscoelastic properties of protein water solutions. Ultimately, this work provides motivation for the integration of computer simulations with experimental data and holds potential for advancing our understanding of both simple and complex systems.